scholarly journals VO2MAX PER BODY MASS PENALIZES THOSE WITH LARGER PERCENT BODY FAT, NOT LARGER LEAN BODY MASS

1995 ◽  
Vol 27 (Supplement) ◽  
pp. S97 ◽  
Author(s):  
P. Vanderburgh ◽  
F. Katch
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Percent Body Fat

scholarly journals Body Morphometrics in NAFLD Population

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Harkeerat Dhami ◽  
Niharika Samala
Keyword(s):  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Percent Body Fat ◽  
Composition Analysis ◽  
Processed Meat ◽  
Body Fat Mass ◽  
High Sodium ◽  
Obstructive Sleep

Introduction: NAFLD is one of the common causes of liver disease in the US and is commonly associated with metabolic syndrome. Among obese, prevalence of NAFLD is 7090%. We wanted to determine body morphometrics in NAFLD. Methods: All individuals presenting to Indiana University Hospital with NAFLD were approached to participate in cross-sectional study. All participants were offered beverage, diet (REAP) questionnaires and body composition analysis using InBody 570, which utilizes bioelectrical impedance. Results: Of the 321 NAFLD individuals enrolled, 256 completed body morphometric analysis. Mean age of the cohort was 51.58 ± 13.54, 58% were female, 297 White and had a mean BMI of 35.92. 76% were obese, 48% had type 2 diabetes, 49.2% had hypertension, 38.6% had dyslipidemia, and 20.5% had obstructive sleep apnea. Despite having similar BMI, females had lower lean body mass (51.01 vs 70.51) and skeletal muscle mass (28.05 vs 39.70), higher body fat mass (46.71 vs 41.04) and percent body fat (46.59 vs. 35.7). Regular coffee consumers had lower BMI (35.3 vs 38, p=0.038), but lower body fat mass (39.9 vs 46.2, p=0.01), percent body fat (41.1 vs 44.4, p=0.05) and higher lean body mass % (58.8 vs 55.5, p=0.049). Processed meat consumption was associated with higher BMI (39 vs 35.3, P=0.01), percent body fat (45.5 vs 42, p=0.04), and lower lean body mass percentage (54.5 vs 58.2, P=0.04). Similar trends were seen with consumption of high sodium processed foods and watching television for ≥ 2 hours/day. Conclusion: Among individuals with NAFLD, we saw a higher female preponderance, who were found to have unfavorable body morphometrics despite similar BMI as males. Consumption of high sodium processed food and meat and excess screen time have unfavorable, while regular coffee drinkers have favorable body morphometrics, which offer modifiable measures for risk factors associated with NAFLD.

Abstract P246: Lean Body Mass, Percent Body Fat, and HbA1c in the U.S. Population: The National Health and Nutrition Examination Survey (NHANES 1999-2006)

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Julie K Bower ◽  
Rachel Brackett ◽  
Meredith C Foster ◽  
Randi E Foraker
Keyword(s):  
Weight Loss ◽  
Waist Circumference ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Lean Mass ◽  
Diabetes Prevention ◽  
Percent Body Fat ◽  
Race Ethnicity ◽  
Diagnosed Diabetes

Introduction: Weight loss is an important component of diabetes prevention and management because of the known effect of adiposity on insulin resistance. While both muscle (lean mass) and fat mass are known to serve important metabolic functions, most studies of obesity and diabetes use proxy measures for overall or abdominal obesity without accounting for the composition of that mass. The aim of this study was to examine the association of total and trunk lean body mass and fat mass with hemoglobin A1c (HbA1c) - an indicator of glucose control in persons with diabetes and a risk marker in non-diabetic populations - in the general U.S. population. Methods: We conducted a cross-sectional analysis of data from the NHANES collected in 1999-2006 in participants aged 18-69 years. Lean body mass and percent body fat were determined using dual energy x-ray absorptiometry (DXA); analyses were weighted and multiple imputation was applied to account for missing DXA data. Associations of body composition with HbA1C were evaluated using multiple linear regression. Results: The study sample included 1,085 participants with diagnosed diabetes (mean age 56 years, 50% male, mean HbA1c=7.6%) and 15,597 participants without diabetes (mean age 40 years, 51% women, mean HbA1c=5.3%). Trunk lean mass and total lean mass were significantly associated with lower HbA1c in adults without diabetes, independent of body mass index (BMI) and waist circumference. After adjustment for age, sex, race/ethnicity, and waist circumference, each 10 kg increase in trunk lean mass was associated with 0.07-% points lower HbA1c (95% CI: -0.09, -0.03). After adjustment for age, sex, race/ethnicity, and BMI, each 10kg increase in total lean mass was associated with 0.03-% points lower HbA1c (95% CI: -0.05, -0.0). Each 5% increase in trunk fat was associated with 0.5-% point higher HbA1c (95% CI: 0.45, 0.55) and each 5% increase in total fat was associated with 0.05-% point higher HbA1c (95% CI: 0.05, 0.06). Lean mass and percent body fat were not associated with HbA1c in participants with diagnosed diabetes (p > 0.05). Conclusions: Lean mass is independently associated with HbA1c in adults without diabetes. Interventions that target both weight loss where warranted and increasing lean mass via resistance training may have the most beneficial impact for diabetes prevention.

scholarly journals Relationship between body fat, lean body mass and disease severity in AECOPD patients

2021 ◽  
Author(s):  
Yiben Huang ◽  
Jiedong Ma ◽  
Xueting Hu ◽  
Jianing Wang ◽  
Xiaqi Miao ◽  
...  
Keyword(s):  
Disease Severity ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat

Comparison of the Effect of Soy protein and Whey protein on Body Composition: A Meta-Analysis of Randomized Clinical Trials

2021 ◽  
pp. 1-27
Author(s):  
Masoome Piri Damaghi ◽  
Atieh Mirzababaei ◽  
Sajjad Moradi ◽  
Elnaz Daneshzad ◽  
Atefeh Tavakoli ◽  
...  
Keyword(s):  
Body Composition ◽  
Whey Protein ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Fat Mass ◽  
Soy Protein ◽  
Protein Supplementation ◽  
Body Fat Percentage ◽  
Fat Percentage

Abstract Background: Essential amino acids (EAAs) promote the process of regulating muscle synthesis. Thus, whey protein that contains higher amounts of EAA can have a considerable effect on modifying muscle synthesis. However, there is insufficient evidence regarding the effect of soy and whey protein supplementation on body composition. Thus, we sought to perform a meta-analysis of published Randomized Clinical Trials that examined the effect of whey protein supplementation and soy protein supplementation on body composition (lean body mass, fat mass, body mass and body fat percentage) in adults. Methods: We searched PubMed, Scopus, and Google Scholar, up to August 2020, for all relevant published articles assessing soy protein supplementation and whey protein supplementation on body composition parameters. We included all Randomized Clinical Trials that investigated the effect of whey protein supplementation and soy protein supplementation on body composition in adults. Pooled means and standard deviations (SD) were calculated using random-effects models. Subgroup analysis was applied to discern possible sources of heterogeneity. Results: After excluding non-relevant articles, 10 studies, with 596 participants, remained in this study. We found a significant increase in lean body mass after whey protein supplementation weighted mean difference (WMD: 0.91; 95% CI: 0.15, 1.67. P= 0.019). Subgroup analysis, for whey protein, indicated that there was a significant increase in lean body mass in individuals concomitant to exercise (WMD: 1.24; 95% CI: 0.47, 2.00; P= 0.001). There was a significant increase in lean body mass in individuals who received 12 or less weeks of whey protein (WMD: 1.91; 95% CI: 1.18, 2.63; P<0.0001). We observed no significant change between whey protein supplementation and body mass, fat mass, and body fat percentage. We found no significant change between soy protein supplementation and lean body mass, body mass, fat mass, and body fat percentage. Subgroup analysis for soy protein indicated there was a significant increase in lean body mass in individuals who supplemented for 12 or less weeks with soy protein (WMD: 1.48; 95% CI: 1.07, 1.89; P< 0.0001). Conclusion: Whey protein supplementation significantly improved body composition via increases in lean body mass, without influencing fat mass, body mass, and body fat percentage.

Limitations of body mass index for counseling individuals with unilateral lower extremity amputation

2016 ◽  
Vol 41 (2) ◽  
pp. 186-193 ◽  
Author(s):  
Alexandra P Frost ◽  
Tracy Norman Giest ◽  
Allison A Ruta ◽  
Teresa K Snow ◽  
Mindy Millard-Stafford
Keyword(s):  
Body Mass Index ◽  
Lower Extremity ◽  
Health Risk ◽  
Body Mass ◽  
Body Fat ◽  
Lower Limb ◽  
Dual Energy ◽  
Limb Loss ◽  
Percent Body Fat ◽  
X Ray

Background: Body composition is important for health screening, but appropriate methods for unilateral lower extremity amputees have not been validated. Objectives: To compare body mass index adjusted using Amputee Coalition equations (body mass index–Amputee Coalition) to dual-energy X-ray absorptiometry in unilateral lower limb amputees. Study design: Cross-sectional, experimental. Methods: Thirty-eight men and women with lower limb amputations (transfemoral, transtibial, hip disarticulation, Symes) participated. Body mass index (mass/height2) was compared to body mass index corrected for limb loss (body mass index–Amputee Coalition). Accuracy of classification and extrapolation of percent body fat with body mass index was compared to dual-energy X-ray absorptiometry. Results: Body mass index–Amputee Coalition increased body mass index (by ~ 1.1 kg/m2) but underestimated and mis-classified 60% of obese and overestimated 100% of lean individuals according to dual-energy X-ray absorptiometry. Estimated mean percent body fat (95% confidence interval) from body mass index–Amputee Coalition (28.3% (24.9%, 31.7%)) was similar to dual-energy X-ray absorptiometry percent body fat (29.5% (25.2%, 33.7%)) but both were significantly higher ( p < 0.05) than percent body fat estimated from uncorrected body mass index (23.6% (20.4%, 26.8%)). However, total errors for body mass index and body mass index–Amputee Coalition converted to percent body fat were unacceptably large (standard error of the estimate = 6.8%, 6.2% body fat) and the discrepancy between both methods and dual-energy X-ray absorptiometry was inversely related ( r = −0.59 and r = −0.66, p < 0.05) to the individual’s level of body fatness. Conclusions: Body mass index (despite correction) underestimates health risk for obese patients and overestimates lean, muscular individuals with lower limb amputation. Clinical relevance Clinical recommendations for an ideal body mass based on body mass index–Amputee Coalition should not be relied upon in lower extremity amputees. This is of particular concern for obese lower extremity amputees whose health risk might be significantly underestimated based on body mass index despite a “correction” formula for limb loss.

Biathlon Performance: Heart Rate, Hit Rate, Speed and Physiological Variables

2021 ◽  
Vol 15 (10) ◽  
pp. 3245-3249
Author(s):  
Gökhan Atasever ◽  
Fatih Kiyici ◽  
Deniz Bedir ◽  
Fatih Ağduman
Keyword(s):  
Heart Rate ◽  
Lean Body Mass ◽  
Body Mass ◽  
Body Fat ◽  
Maximum Speed ◽  
Fat Percentage ◽  
Physiological Variables ◽  
Cross Country Skiing ◽  
Cross Country ◽  
Short Time

Aim: Biathlon is a sport that combines cross-country skiing and rifle shooting. The athlete is fast in the cross-country skiing section, in the gun shooting section, the heart rate should be low. This study aims to determine the hitting rate of the shots made with different training loads on low altitude in elite biathletes in terms of maximum speed and physiological variables. Methods: To evaluate shooting performances first with the resting pulse and then after 2.5 km skiing respectively with 50%, 70% and 100% pulse rate which is separately calculated for each athlete according to karvonen formula. Results: Our findings show that while there was negative relation between maximum speed and body fat there was a positive relation with lean body mass. It has been determined that low body fat percentage and high lean body mass are effective at the athletes’ maximum speed and the pulse level with the highest target shooting accuracy rate was at rest and 70% in the second level. Conclusion: Since the pulse of the athlete who comes to the shooting area cannot be reduced to a resting level in a short time, focusing the 70% pulse zone may be beneficial in terms of shooting accuracy and acceleration after the shot. The lowest results in target shooting accuracy were seen at 50% and 100% loads. Keywords: Athletes, performance, heart, rate, lean body mass.

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